The impact of fragmentation and density regulation on forest succession in the Atlantic rain forest

The Atlantic Rain Forest, an important biodiversity hot spot, has faced severe habitat loss since the last century which has resulted in a highly fragmented landscape with a large number of small forest patches (<100 ha). For conservation planning it is essential to understand how current and future forest regeneration depends on ecological processes, fragment size and the connection to the regional seed pool. We have investigated the following questions by applying the forest growth simulation model FORMIND to the situation of the Atlantic Forest in the state of São Paulo, SE Brazil: (1) which set of parameters describing the local regeneration and level of density regulation can reproduce the biomass distribution and stem density of an old growth forest in a reserve? (2) Which additional processes apart from those describing the dynamics of an old growth forest, drive forest succession of small isolated fragments? (3) Which role does external seed input play during succession? Therefore, more than 300 tree species have been classified into nine plant functional types (PFTs), which are characterized by maximum potential height and shade tolerance. We differentiate between two seed dispersal modes: (i) local dispersal, i.e. all seedlings originated from fertile trees within the simulated area and (ii) external seed rain. Local seed dispersal has been parameterized following the pattern oriented approach, using biomass estimates of old growth forest. We have found that moderate density regulation is essential to achieve coexistence for a broad range of regeneration parameters. Considering the expected uncertainty and variability in the regeneration processes it is important that the forest dynamics are robust to variations in the regeneration parameters. Furthermore, edge effects such as increased mortality at the border and external seed rain have been necessary to reproduce the patterns for small isolated fragments. Overall, simulated biomass is much lower in the fragments compared to the continuous forest, whereas shade tolerant species are affected most strongly by fragmentation. Our simulations can supplement empirical studies by extrapolating local knowledge on edge effects of fragments to larger temporal and spatial scales. In particular our results show the importance of external seed rain and therefore highlight the importance of structural connectivity between regenerating fragments and mature forest stands.     

Reduction of CO2 emission by optimally tracking a pre-defined target

The recent global financial crisis has highlighted the need for balanced and efficient investments in the reduction of the greenhouse effect caused by emissions of CO₂ on a global scale. In a previous paper, the authors proposed a mathematical model describing the dynamic relation of CO₂ emission with investment in reforestation and clean technology. An efficient allocation of resources to reduce the greenhouse effect has also been proposed. Here, this model is used to provide estimates of the investments needed in land reforestation and in the adoption of clean technologies for an optimum emission and abatement of CO₂, for the period of 1996–2014. The required investments are computed to minimize deviations with respect to the emission targets proposed in the Kyoto Protocol for European Countries. The emission target can be achieved by 2014 with investments in reforestation peaking in 2004, and a reduction of the expected GDP of 42%, relative to 2006. Investments in clean technology should increase between 2008 and 2010 with maximum transfer figures around 70 million American dollars. Total (cumulative) costs are, however, relatively high depending on the price of carbon abatement and the rate at which the expected CO₂ concentration in the atmosphere should be reduced. Results highlight the advantages for policy makers to be able to manage investments in climate policy more efficiently, controlling optimum transfers based on a portfolio of actions that tracks a pre-defined CO₂ concentration target.     

What enables coexistence in plant communities? Weak versus strong species traits and the role of local processes

Explaining the coexistence of species that basically depend on the same resources has been a brainteaser for generations of ecologists. Different mechanisms have been proposed to facilitate coexistence in plant communities, where space is an important resource. Using a stochastic cellular automaton simulation model we analyze - separately and in combination - the influence of different species traits and processes which alter local competition on the coexistence of plant species over a fixed time horizon. We show that different species traits operate on different time scales in competition. We therefore suggest the concept of weak versus strong traits according to short- or long-term exclusion of species differing in these traits. As a consequence, highly non-linear trade-offs between weak and strong traits can result in communities. Furthermore, we found that trade-offs based on physiological species traits such as plant lifetime, dispersal range and plant growth, did not support broad and long-term coexistence—further processes such as density-dependent mortality and light-dependent colonization were necessary. This suggests that coexistence in plant communities requires (stabilizing) local processes to support the (equalizing) trade-offs in species traits.     

Predicting a ‘tree change’ in Australia's tropical savannas: Combining different types of models to understand complex ecosystem behaviour

In this study, key ecological modelling limitations of a process-based simulation model and a Bayesian network were reduced by combining the two approaches. We demonstrate the combined modelling approach with a case study investigating increases in woody vegetation density in northern Australia's tropical savannas. We found that by utilising the strengths of a simulation model and a Bayesian network we could both forecast future change in woody vegetation density and diagnose the reasons for current vegetation states. The local conditions of climate, soil characteristics and the starting population of trees were found to be more important in explaining the likelihood of change in woody vegetation density compared to management practices such as grazing pressure and fire regimes. We conclude that combining the strengths of a process and BN model allowed us to produce a simple model that utilised the ability of the process model to simulate ecosystem processes in detail and over long time periods, and the ability of the BN to capture uncertainty in ecosystem response and to conduct scenario, sensitivity and diagnostic analysis. The overall result was a model that has the potential to provide land managers with a better understanding of the behaviour of a complex ecosystem than simply utilising either modelling approach in isolation.     

An evaluation of three statistical methods used to model resource selection

The performance of statistical methods for modeling resource selection by animals is difficult to evaluate with field data because true selection patterns are unknown. Simulated data based on a known probability distribution, though, can be used to evaluate statistical methods. Models should estimate true selection patterns if they are to be useful in analyzing and interpreting field data. We used simulation techniques to evaluate the effectiveness of three statistical methods used in modeling resource selection. We generated 25 use locations per animal and included 10, 20, 40, or 80 animals in samples of use locations. To simulate species of different mobility, we generated use locations at four levels according to a known probability distribution across DeSoto National Wildlife Refuge (DNWR) in eastern Nebraska and western Iowa, USA. We either generated 5 random locations per use location or 10,000 random locations (total) within 4 predetermined areas around use locations to determine how the definition of availability and the number of random locations affected results. We analyzed simulated data using discrete choice, logistic-regression, and a maximum entropy method (Maxent). We used a simple linear regression of estimated and known probability distributions and area under receiver operating characteristic curves (AUC) to evaluate the performance of each method. Each statistical method was affected differently by number of animals and random locations used in analyses, level at which selection of resources occurred, and area considered available. Discrete-choice modeling resulted in precise and accurate estimates of the true probability distribution when the area in which use locations were generated was ≥ the area defined to be available. Logistic-regression models were unbiased and precise when the area in which use locations were generated and the area defined to be available were the same size; the fit of these models improved with increased numbers of random locations. Maxent resulted in unbiased and precise estimates of the known probability distribution when the area in which use locations were generated was small (home-range level) and the area defined to be available was large (study area). Based on AUC analyses, all models estimated the selection distribution better than random chance. Results from AUC analyses, however, often contradicted results of the linear regression method used to evaluate model performance. Discrete-choice modeling was best able to estimate the known selection distribution in our study area regardless of sample size or number of random locations used in the analyses, but we recommend further studies using simulated data over different landscapes and different resource metrics to confirm our results. Our study offers an approach and guidance for others interested in assessing the utility of techniques for modeling resource selection in their study area.     

A method for building spatial model of annual weed seed dispersal from experimental data and its application to simulating Bromus sterilis population dispersal

Spatial model of annual weed seed dispersal, in this article, was theoretically derived. According to the requirements of building the spatial model, we designed and done an indoor experiment of weed seed dispersal by wind. In the experiment, the seeds of Bromus sterilis were released at 100 cm height under different wind velocity conditions. Based on the experimental data, the spatial models of seed dispersal of the weed species were built, which were divided into three types according to the coefficient β < 0, β = 0, β > 0. The results showed that dispersal of annual weed seed in any direction obeyed an approximate Gaussian distribution; under the experimental conditions, spatial distribution type of weed seed dispersal changed with variation of wind velocity. Well-known Howard et al.'s model (Howard et al., 1991) of Bromus sterilis seed dispersal is an especial example of the model built in this article. The result of model analysis indicated that the distribution type described by Howard's model was similar to that of seed dispersal of the weed species at the height of 100 cm under the condition of lower wind velocity (about 2.18 m/s). Using CA simulation analysis we found that mean control agent applying to a cell with weed should have a decrease with an increase of wind velocity to prevent weed with the initial configuration from spreading, which implicated less herbicide needs spraying in every cell with weed on average when wind velocity increases.     

Industrial waste management simulation game and its educational effect

The purposes of this study were to develop the Industrial Waste Game and to examine the validity of this game as a tool for environmental education. The aim of this game is to enable players to understand the social dilemma between individual interest of hazardous dumping and the social cost of purifying pollution, and to find a solution to the social dilemma by providing the monitoring and sanction system for illegal dumping or other efficient systems. The game was played by 213 undergraduate students who were divided into 40 groups of 5 to 6 people. One of 4 combinations of monitoring and penalty conditions was assigned to each group. The players were asked to answer questionnaires concerning their interests and understanding of the industrial waste issue before and after the game to evaluate educational effects. The results indicated that the players increased their awareness of industrial waste problems and came to understand that these problems were caused not by psychological factors such as immorality of the illegal dumper but mainly by social structural factors like the social dilemma. Through playing the game and participating in post-game discussion, players were able to obtain interesting experience and gain motivation to learn more.     

模具成形过程中虚拟仿真环境研究

此文提出了一种基于先进制造技术、并行工程、知识工程及网络技术于一体的虚拟仿真系统思想——VS,对其组织方式、结构模型、环境关键技术和发展前景作了尝试性地探讨研究。这将有助于整个模具制造业找到一个新的应用发展突破点,真正体现高速、高效、高质的优势。     

工业危险源仿真预警技术

概述了应用数字仿真技术于液化天然气风险评价、蒸汽云爆炸后果预测以及液氨储罐泄漏监控预警系统等的国内外研究与发展现状，给出了计算机仿真结果和现场实测数据之间的对比曲线。     

生态动力学模型在太湖水质模拟中的应用

考察了西澳大利亚大学水研究中心开发的生态动力学模型CAEDYM与三维水动力模型ELCOM的耦合模型在太湖的应用效果,用该模型模拟了2005年5月~6月太湖的水温、总氮、硝氮、氨氮、总磷、磷酸盐、叶绿素a,通过实测数据进行参数率定。并用2005年8月的实测资料作为初始条件,9月的模拟资料与实测资料进行对比,对模型进行了验证。结果显示模型较好地模拟了太湖的水质变化和分布。